Особливості застосування механізму уваги (attention) у класифікації музичних творів

Abstract

The article examines the attention mechanism as an innovative approach to music classification. It describes the process of identifying relevant parts of audio signals to improve model accuracy. Importance scoring, attention weight normalization, and context vector computation are discussed. An example of attention implementation in recurrent neural networks (RNN) is provided, showcasing its advantages for analyzing complex musical structures.